






from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__UpperCamelCase   :   List[str]      =    logging.get_logger(__name__)

__UpperCamelCase   :   Tuple      =    {
    """google/bigbird-roberta-base""": """https://huggingface.co/google/bigbird-roberta-base/resolve/main/config.json""",
    """google/bigbird-roberta-large""": """https://huggingface.co/google/bigbird-roberta-large/resolve/main/config.json""",
    """google/bigbird-base-trivia-itc""": """https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/config.json""",
    # See all BigBird models at https://huggingface.co/models?filter=big_bird
}


class 							__UpperCamelCase     (  _lowerCAmelCase ):
	__snake_case						:List[Any] =							'big_bird'







	def __init__(	self   :				str							,					_lowerCAmelCase   :				Any=5_0358							,					_lowerCAmelCase   :				Optional[int]=768							,					_lowerCAmelCase   :				Union[str, Any]=12							,					_lowerCAmelCase   :				Optional[int]=12							,					_lowerCAmelCase   :				Optional[Any]=3072							,					_lowerCAmelCase   :				List[str]="gelu_new"							,					_lowerCAmelCase   :				Optional[Any]=0.1							,					_lowerCAmelCase   :				int=0.1							,					_lowerCAmelCase   :				Optional[int]=4096							,					_lowerCAmelCase   :				Any=2							,					_lowerCAmelCase   :				List[Any]=0.02							,					_lowerCAmelCase   :				List[Any]=1e-12							,					_lowerCAmelCase   :				List[Any]=True							,					_lowerCAmelCase   :				Union[str, Any]=0							,					_lowerCAmelCase   :				Tuple=1							,					_lowerCAmelCase   :				Dict=2							,					_lowerCAmelCase   :				Optional[int]=66							,					_lowerCAmelCase   :				Dict="block_sparse"							,					_lowerCAmelCase   :				Optional[int]=True							,					_lowerCAmelCase   :				str=False							,					_lowerCAmelCase   :				str=64							,					_lowerCAmelCase   :				Union[str, Any]=3							,					_lowerCAmelCase   :				Union[str, Any]=None							,					**_lowerCAmelCase   :				List[Any]							,					)		->			Union[str, Any]:
		"""simple docstring"""







		super().__init__(
		    pad_token_id=_lowerCAmelCase							,					bos_token_id=_lowerCAmelCase							,					eos_token_id=_lowerCAmelCase							,					sep_token_id=_lowerCAmelCase							,					**_lowerCAmelCase							,					)

		__lowercase   							=	vocab_size
		__lowercase   							=	max_position_embeddings
		__lowercase   							=	hidden_size
		__lowercase   							=	num_hidden_layers
		__lowercase   							=	num_attention_heads
		__lowercase   							=	intermediate_size
		__lowercase   							=	hidden_act
		__lowercase   							=	hidden_dropout_prob
		__lowercase   							=	attention_probs_dropout_prob
		__lowercase   							=	initializer_range
		__lowercase   							=	type_vocab_size
		__lowercase   							=	layer_norm_eps
		__lowercase   							=	use_cache

		__lowercase   							=	rescale_embeddings
		__lowercase   							=	attention_type
		__lowercase   							=	use_bias
		__lowercase   							=	block_size
		__lowercase   							=	num_random_blocks
		__lowercase   							=	classifier_dropout


class 							__UpperCamelCase     (  _lowerCAmelCase ):







	@property
	def 			_a (	self   :				List[str]      )		->			Mapping[str, Mapping[int, str]]:
		"""simple docstring"""







		if self.task == "multiple-choice":
			__lowercase   							=	{0: """batch""", 1: """choice""", 2: """sequence"""}
		else:
			__lowercase   							=	{0: """batch""", 1: """sequence"""}
		return OrderedDict(
		    [
		        ("""input_ids""", dynamic_axis),
		        ("""attention_mask""", dynamic_axis),
		    ]      )








"""simple docstring"""





import os
import shutil
from pathlib import Path
from typing import Optional, Union

import numpy as np
from huggingface_hub import hf_hub_download

from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging


if is_onnx_available():
       import onnxruntime as ort


SCREAMING_SNAKE_CASE__   =  logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__   =  {
    "tensor(bool)": np.bool_,
    "tensor(int8)": np.inta,
    "tensor(uint8)": np.uinta,
    "tensor(int16)": np.intaa,
    "tensor(uint16)": np.uintaa,
    "tensor(int32)": np.intaa,
    "tensor(uint32)": np.uintaa,
    "tensor(int64)": np.intaa,
    "tensor(uint64)": np.uintaa,
    "tensor(float16)": np.floataa,
    "tensor(float)": np.floataa,
    "tensor(double)": np.floataa,
}

class 						lowercase   :





      def __init__(			self ,		lowercase=None ,		**lowercase					)						->	int:
            logger.info("""`diffusers.OnnxRuntimeModel` is experimental and might change in the future."""					)
            lowerCAmelCase    		=			model
            lowerCAmelCase    		=			kwargs.get("""model_save_dir""" ,		lowercase					)
            lowerCAmelCase    		=			kwargs.get("""latest_model_name""" ,		lowercase					)





      def __call__(			self ,		**lowercase					)						->	List[Any]:
            lowerCAmelCase    		=			{k: np.array(lowercase					) for k, v in kwargs.items()}
            return self.model.run(lowercase ,		lowercase					)





      @staticmethod
      def        _snake_case     (			lowercase ,		lowercase=None ,		lowercase=None					)						->	Optional[Any]:
            if provider is None:
                  logger.info("""No onnxruntime provider specified, using CPUExecutionProvider"""					)
                  lowerCAmelCase    		=			"""CPUExecutionProvider"""

            return ort.InferenceSession(lowercase ,		providers=[provider] ,		sess_options=lowercase					)





      def        _snake_case     (			self ,		lowercase ,		lowercase = None ,		**lowercase					)						->	str:
            lowerCAmelCase    		=			file_name if file_name is not None else ONNX_WEIGHTS_NAME

            lowerCAmelCase    		=			self.model_save_dir.joinpath(self.latest_model_name					)
            lowerCAmelCase    		=			Path(lowercase					).joinpath(lowercase					)
            try:
                  shutil.copyfile(lowercase ,		lowercase					)
            except shutil.SameFileError:
                  pass

            # copy external weights (for models >2GB)
            lowerCAmelCase    		=			self.model_save_dir.joinpath(lowercase					)
            if src_path.exists():
                  lowerCAmelCase    		=			Path(lowercase					).joinpath(lowercase					)
                  try:
                        shutil.copyfile(lowercase ,		lowercase					)
                  except shutil.SameFileError:
                        pass





      def        _snake_case     (			self ,		lowercase ,		**lowercase ,		)						->	str:
            if os.path.isfile(lowercase					):
                  logger.error(f'Provided path ({save_directory}) should be a directory, not a file'					)
                  return

            os.makedirs(lowercase ,		exist_ok=lowercase					)

            # saving model weights/files
            self._save_pretrained(lowercase ,		**lowercase					)





      @classmethod
      def        _snake_case     (			cls ,		lowercase ,		lowercase = None ,		lowercase = None ,		lowercase = False ,		lowercase = None ,		lowercase = None ,		lowercase = None ,		lowercase = None ,		**lowercase ,		)						->	Union[str, Any]:
            lowerCAmelCase    		=			file_name if file_name is not None else ONNX_WEIGHTS_NAME
            # load model from local directory
            if os.path.isdir(lowercase					):
                  lowerCAmelCase    		=			OnnxRuntimeModel.load_model(
                      os.path.join(lowercase ,		lowercase					) ,		provider=lowercase ,		sess_options=lowercase					)
                  lowerCAmelCase    		=			Path(lowercase					)
            # load model from hub
            else:
                  # download model
                  lowerCAmelCase    		=			hf_hub_download(
                      repo_id=lowercase ,		filename=lowercase ,		use_auth_token=lowercase ,		revision=lowercase ,		cache_dir=lowercase ,		force_download=lowercase ,		)
                  lowerCAmelCase    		=			Path(lowercase					).parent
                  lowerCAmelCase    		=			Path(lowercase					).name
                  lowerCAmelCase    		=			OnnxRuntimeModel.load_model(lowercase ,		provider=lowercase ,		sess_options=lowercase					)
            return cls(model=lowercase ,		**lowercase					)





      @classmethod
      def        _snake_case     (			cls ,		lowercase ,		lowercase = True ,		lowercase = None ,		lowercase = None ,		**lowercase ,		)						->	List[str]:
            lowerCAmelCase    		=			None
            if len(str(lowercase					).split("""@"""					)					) == 2:
                  lowerCAmelCase		,						lowerCAmelCase    		=			model_id.split("""@"""					)

            return cls._from_pretrained(
                model_id=lowercase ,		revision=lowercase ,		cache_dir=lowercase ,		force_download=lowercase ,		use_auth_token=lowercase ,		**lowercase ,		)






